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Investigation of nonlinear accelerated degradation mechanism in fuel cell stack under dynamic driving cycles from polarization processes

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  • Zhang, Xuexia
  • Huang, Lei
  • Jiang, Yu
  • Lin, Long
  • Liao, Hongbo
  • Liu, Wentao

Abstract

The nonlinear accelerated degradation severely limits the lifetime of fuel cells. This paper presents a comprehensive analysis of polarization processes during accelerated performance degradation. The double trap model is applied to reveal kinetic degradation, and an equivalent circuit model based on the distribution of relaxation times is proposed to identify and quantify the polarization loss and low-frequency inductive loop. Combined with monitoring dynamic voltage, the results show that the accelerated performance decline is dominated by the growth of platinum oxides rather than kinetic degradation and structural damage. The platinum oxides reduce the cathode mixed potential gradually, leading to the accelerated decay occurring earlier at low current density. Meanwhile, the high oxide coverage hinders oxygen diffusion and water removal, resulting in sudden and drastic concentration polarization in the high current density region. Furthermore, the formation and reduction of platinum oxide affect voltage stability and steady performance of loading and unloading processes due to their potential dependency. The present study helps in modeling and predicting the nonlinear accelerated ageing to improve the lifetime of fuel cells.

Suggested Citation

  • Zhang, Xuexia & Huang, Lei & Jiang, Yu & Lin, Long & Liao, Hongbo & Liu, Wentao, 2024. "Investigation of nonlinear accelerated degradation mechanism in fuel cell stack under dynamic driving cycles from polarization processes," Applied Energy, Elsevier, vol. 355(C).
  • Handle: RePEc:eee:appene:v:355:y:2024:i:c:s0306261923016501
    DOI: 10.1016/j.apenergy.2023.122286
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    1. Benaggoune, Khaled & Yue, Meiling & Jemei, Samir & Zerhouni, Noureddine, 2022. "A data-driven method for multi-step-ahead prediction and long-term prognostics of proton exchange membrane fuel cell," Applied Energy, Elsevier, vol. 313(C).
    2. Yuan, Hao & Dai, Haifeng & Ming, Pingwen & Wang, Xueyuan & Wei, Xuezhe, 2021. "Quantitative analysis of internal polarization dynamics for polymer electrolyte membrane fuel cell by distribution of relaxation times of impedance," Applied Energy, Elsevier, vol. 303(C).
    3. Mohideen, Mohamedazeem M. & Subramanian, Balachandran & Sun, Jingyi & Ge, Jing & Guo, Han & Radhamani, Adiyodi Veettil & Ramakrishna, Seeram & Liu, Yong, 2023. "Techno-economic analysis of different shades of renewable and non-renewable energy-based hydrogen for fuel cell electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 174(C).
    4. Pei, Pucheng & Chen, Dongfang & Wu, Ziyao & Ren, Peng, 2019. "Nonlinear methods for evaluating and online predicting the lifetime of fuel cells," Applied Energy, Elsevier, vol. 254(C).
    5. Zhao, Lei & Yuan, Hao & Xie, Jiaping & Jiang, Shangfeng & Wei, Xuezhe & Tang, Wei & Ming, Pingwen & Dai, Haifeng, 2023. "Inconsistency evaluation of vehicle-oriented fuel cell stacks based on electrochemical impedance under dynamic operating conditions," Energy, Elsevier, vol. 265(C).
    6. Hu, Zunyan & Xu, Liangfei & Huang, Yiyuan & Li, Jianqiu & Ouyang, Minggao & Du, Xiaoli & Jiang, Hongliang, 2018. "Comprehensive analysis of galvanostatic charge method for fuel cell degradation diagnosis," Applied Energy, Elsevier, vol. 212(C), pages 1321-1332.
    7. Liu, Hao & Chen, Jian & Hissel, Daniel & Lu, Jianguo & Hou, Ming & Shao, Zhigang, 2020. "Prognostics methods and degradation indexes of proton exchange membrane fuel cells: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 123(C).
    8. Zhao, Lei & Hong, Jichao & Xie, Jiaping & Jiang, Shangfeng & Wei, Xuezhe & Ming, Pingwen & Dai, Haifeng, 2023. "Investigation of local sensitivity for vehicle-oriented fuel cell stacks based on electrochemical impedance spectroscopy," Energy, Elsevier, vol. 262(PA).
    9. Pei, Pucheng & Meng, Yining & Chen, Dongfang & Ren, Peng & Wang, Mingkai & Wang, Xizhong, 2023. "Lifetime prediction method of proton exchange membrane fuel cells based on current degradation law," Energy, Elsevier, vol. 265(C).
    10. Meng, Kai & Chen, Ben & Zhou, Haoran & Shen, Jun & Shen, Zuguo & Tu, Zhengkai, 2022. "Investigation on degradation mechanism of hydrogen–oxygen proton exchange membrane fuel cell under current cyclic loading," Energy, Elsevier, vol. 242(C).
    11. Jouin, Marine & Gouriveau, Rafael & Hissel, Daniel & Péra, Marie-Cécile & Zerhouni, Noureddine, 2016. "Degradations analysis and aging modeling for health assessment and prognostics of PEMFC," Reliability Engineering and System Safety, Elsevier, vol. 148(C), pages 78-95.
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    Cited by:

    1. Song, Ke & Huang, Xing & Huang, Pengyu & Sun, Hui & Chen, Yuhui & Huang, Dongya, 2024. "Data-driven health state estimation and remaining useful life prediction of fuel cells," Renewable Energy, Elsevier, vol. 227(C).
    2. Maestre, V.M. & Ortiz, A. & Ortiz, I., 2024. "Sustainable and self-sufficient social home through a combined PV‑hydrogen pilot," Applied Energy, Elsevier, vol. 363(C).

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